ARIMA Models in Python

via

DataCamp

Course Features

Duration

4 hours

Delivery Method

Online

Available on

Limited Access

Accessibility

Mobile, Desktop, Laptop

Language

English

Subtitles

English

Level

Intermediate

Teaching Type

Self Paced

Video Content

4 hours

Course Description

Are you able to predict the future? It's difficult to predict what the future will look like. This course will show you how to use powerful ARIMA classes models to predict the future. This course will show you how to use statsmodels for analysis of time series and to create customized models. This course also teaches how to forecast in uncertainty. What is the stock market's movements over the next 24 hours? What will the effect of increasing levels of CO2 in the next decade? How many earthquakes will there be in the coming year? These and other problems will all be solved.

Course Overview

Virtual Labs

International Faculty

Post Course Interactions

Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

Supervised Learning with scikit-learn

What You Will Learn

Learn about ARIMA models in Python and become an expert in time series analysis

You will learn how to use the statsmodels package to analyze time series, to build tailored models, and to forecast under uncertainty

Course Content

Expand all sections

Module 1: Chapter 1 - ARMA Models

Module 2: Chapter 2 - Fitting the Future

Module 3: Chapter 3 - The Best of the Best Models

Module 4: Chapter 4 - Seasonal ARIMA Models

Course Instructors

James Fulton

Climate Informatics Researcher

James is a PhD researcher at the University of Edinburgh, where he tutors computing, machine learning, data analysis, and statistical physics. His research involves using and developing machine learn...